📅 2025-04-18 — Session: Architected PromptFlow Engine for AI Workflows
🕒 18:00–18:35
🏷️ Labels: Promptflow, Architecture, Ai Workflows, Modular Design, Python
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal:
The session aimed to define and outline the architecture of the PromptFlow Engine, a modular orchestration framework for AI workflows using YAML-defined flows and reusable building blocks.
Key Activities:
- Architecture Definition: Discussed the architecture of the PromptFlow Engine, emphasizing its modular design and the use of YAML for defining workflows.
- Overview and Planning: Provided an overview of the PromptFlow architecture, detailing its open-source nature and developer tooling interfaces.
- Core Architectural Pillars: Outlined the seven core architectural pillars of PromptFlow, focusing on modularity, composability, and scalability.
- Script Analysis and Decomposition: Analyzed and decomposed scripts into executable snippets, aligning them with PromptFlow’s architectural pillars.
- Mapping and Execution: Mapped AI workflow scripts to PromptFlow pillars, highlighting the functionality of each code segment.
- Python Block Organization: Structured shared Python blocks for clarity and usability within the AI flow engine.
Achievements:
- Successfully defined the architecture of the PromptFlow Engine.
- Mapped AI workflows and scripts to the core architectural pillars.
- Enhanced the organization of Python blocks for better workflow execution.
Pending Tasks:
- Further refinement of the modular components and interfaces.
- Implementation of suggested refactoring directions for scripts.
- Testing and validation of the PromptFlow Engine with real-world AI workflows.